Forecasting neutrino masses from combining KATRIN and the CMB: Frequentist and Bayesian analyses

dc.creatorHost, Ole
dc.creatorLahav, Ofer
dc.creatorAbdalla, Filipe B.
dc.creatorEitel, Klaus
dc.date2007-09-10
dc.date.accessioned2026-07-07T11:19:14Z
dc.date.available2026-07-07T11:19:14Z
dc.descriptionWe present a showcase for deriving bounds on the neutrino masses from laboratory experiments and cosmological observations. We compare the frequentist and Bayesian bounds on the effective electron neutrino mass m_beta which the KATRIN neutrino mass experiment is expected to obtain, using both an analytical likelihood function and Monte Carlo simulations of KATRIN. Assuming a uniform prior in m_beta, we find that a null result yields an upper bound of about 0.17 eV at 90% confidence in the Bayesian analysis, to be compared with the frequentist KATRIN reference value of 0.20 eV. This is a significant difference when judged relative to the systematic and statistical uncertainties of the experiment. On the other hand, an input m_beta=0.35 eV, which is the KATRIN 5sigma detection threshold, would be detected at virtually the same level. Finally, we combine the simulated KATRIN results with cosmological data in the form of present (post-WMAP) and future (simulated Planck) observations. If an input of m_beta=0.2 eV is assumed in our simulations, KATRIN alone excludes a zero neutrino mass at 2.2sigma. Adding Planck data increases the probability of detection to a median 2.7sigma. The analysis highlights the importance of combining cosmological and laboratory data on an equal footing.
dc.description8 pages, 7 figures, uses Revtex. Submitted to PRD
dc.identifierhttps://arxiv.org/abs/0709.1317
dc.identifierhttp://arxiv.org/abs/0709.1317
dc.identifierPhys.Rev.D76:113005,2007
dc.identifierdoi:10.1103/PhysRevD.76.113005
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/193615
dc.subjectHigh Energy Physics - Phenomenology
dc.subjectAstrophysics
dc.titleForecasting neutrino masses from combining KATRIN and the CMB: Frequentist and Bayesian analyses
dc.typetext

Files

Collections